Data Science for Engineers

(3 Credit Hours) · Undergraduate

This course provides a comprehensive introduction to the principles and practices of Data Science. Students will develop intermediate proficiency in Python, enabling them to design and implement effective data science workflows. Key topics include data sourcing, curation, and engineering (such as filtering, storage, and selection). The course also covers modern data visualization techniques, alongside foundational concepts in inference, including classification and regression. Additionally, students will learn to construct compelling narratives and stories using the insights gained from data science processes. Additional comments: This 6-week class will have the following time allocation: 1. Programming skill level-up (Python) (1 week) 2. Data engineering: sourcing, import, transform, clean, store (1 week) 3. Data to inference: regression and classification (3 weeks) 4. Visualization and storytelling (1 week) Assessment will include weekly assignments or quizzes that will build on one another.